This paper proposes a new region-based image retrieval technique
called Principal Regions Image Retrieval (PRIR). This technique
starts by segmenting an image to the most general principal regions
and applies a fuzzy feature histogram to describe the color and
texture properties of each segmented region. The proposed approach
starts by generating a nearest neighbor graph for the segmented
regions, and applying a greedy graph matching algorithm with a
modified scoring function to determine the image rank. The
proposed segmentation approach provides significant speedup
toward state of the art techniques while keeping accurate precision.
Moreover, the proposed approach combines local and global
description to improve the retrieval results. Standard image
databases are used to evaluate the performance of the proposed
system. Results show that the proposed approach enhances the
accuracy of retrieval compared to other approaches reported in the
literature |
